• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.265-273
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• 2022

Waxy corn (Zea mays L.), which contains homozygous mutant alleles for the waxy1 (wx1) gene, is widely consumed as a snack food in Asia. This study evaluated sixteen agronomic characteristics of inbred Korean waxy corn lines to aid development of high-quality waxy corn cultivars. The plant materials studied were 177 inbred waxy corn lines developed by the National Institute of Crop Science, Rural Development Administration, Republic of Korea. For the tested lines, days to tasseling and silking averaged 77.69±2.22 days (with a range of 56-97 days), and 81.12±7.56 days (66-99 days), respectively. Plant length ranged from 88 to 237 cm (averaged 164.88±22.67 cm), ear length averaged 11.75±2.52 cm (5.0-18.5 cm), and ear width averaged 2.94±0.68 cm (1.4-4.5 cm). The number of rows on each ear of corn averaged 12.22±2.22 (7-32 rows) and the kernel number averaged 24.30±4.22 (9-37 kernels) per row. The crude protein content was 12.05±1.53% (8.90-21.80%) and total starch content was 69.27±5.74% (49.5-83.9%). Principal component analysis revealed that ear width, grain length, ear length, days to tasseling, days to silking, percentage of ear setting height, and total starch are features that allow distinction between the 177 waxy inbred corn lines. Hierarchical cluster analysis identified twelve waxy inbred lines that produce tall plants and have a short silking period. These lines may improve yield among quickly growing corn varieties.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.417-426
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• 2023

Rapid climate change has resulted in glacial retreat and increased meltwater inputs in the Antarctic Peninsula, including King George Island where Marian Cove is located. Consequently, these phenomena are expected to induce changes in the water column light properties, which in turn will affect phytoplankton communities. To comprehend the effects of glacial retreat on the marine ecosystem in Marian Cove, we investigated on phytoplankton biomass (chlorophyll-a, chl-a) and various environment parameters in this area in December 2021 and January 2022. The average temperature at the euphotic depth in January 2022 (1.41 ± 0.13 ℃) was higher than that in December 2021 (0.87 ± 0.17 ℃). Contrastingly, the average salinity was lower in January 2022 (33.9 ± 0.10 psu) than in December 2021 (34.1 ± 0.12 psu). Major nutrients, including dissolved inorganic nitrogen, phosphate, and silicate, were sufficiently high, and thus, did not act as limiting factors for phytoplankton biomass. In December 2021 and January 2022, the mean chl-a concentrations were 1.03 ± 0.64 and 0.66 ± 0.15㎍ L^-1, respectively. The mean concentration of suspended particulate matter (SPM) was 24.9 ± 3.54 mgL^-1 during the study period, with elevated values observed in the vicinity of the inner glacier. However, relative lower chl-a concentrations were observed near the inner glacier, possibly due to high SPM load from the glacier, resulting in reduced light attenuation by SPM shading. Furthermore, the proportion of nanophytoplankton exceeded 70% in the inner cove, contributing to elevated mean fractions of nanophytoplankton in the glacier retreat marine ecosystem. Overall, our study indicated that freshwater and SPM inputs from glacial meltwater may possibly act as main factors controlling the dynamics of phytoplankton communities in glacier retreat areas. The findings may also serve as fundamental data for better understanding the carbon cycle in Marian Cove.

• Korean Journal of School Psychology
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• v.16 no.3
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• pp.433-451
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• 2019

This study aimed to develop and validate the Classroom Problem Behavior Scale - Elementary School Version (CPBS-E) measure which is unique to classroom problem behavior exhibited by Korean elementary school students. The focus was on developing a universal screening instrument designed to identify and provide intervention to students who are at-risk for severe social-emotional and behavioral problems. Items were initially drawn from the literature, interviews with elementary school teachers, common office discipline referral measures used in U.S. elementary schools, penalty point systems used in Korean schools, 'Green Mileage', and the Inventory of Emotional and Behavioral Traits. The content validity of the initially developed items was assessed by six classroom and subject teachers, which resulted in the development of a preliminary scale consisting of 63 two-dimensional items (i.e., Within Classroom Problem Behavior and Outside of Classroom Problem Behavior), each of which consisted of 3 to 4 factors. The Within Classroom Problem Behavior dimension consisted of 4 subscales (not being prepared for class, class disruption, aggression, and withdrawn) and the Outside of Classroom Problem Behavior dimension consisted of 3 subscales (rule-violation, aggression, and withdrawn). The CPBS-E was pilot tested on a sample of 154 elementary school students, which resulted in reducing the scale to 23 items. Following the scale revision, the CPBS-E was validated on a sample population of 209 elementary school students. The validation results indicated that the two-dimensional CPBS-E scale of classroom problem behavior was a reliable and valid measure. The test-retest reliability was stable at above .80 in most of the subscales. The CPBS-E measure demonstrated high internal consistency of .76-.94. In examining the criterion validity, the scale's correlation with the Teacher Observation of Classroom Adaptation-Checklist (TOCA-C) was high and the aggression and withdrawn subscales of the CPBS-E demonstrated high correlations with externalization and internalization, respectively, of the Child Behavior Checklist - Teacher Report Form CBCL-TRF). In addition, the factor structure of the CPBS-E scale was examined using the structural equation model and found to be acceptable. The results are discussed in relation to implications, contributions to the field, and limitations.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.4
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• pp.305-314
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• 2007

We studied spatial and temporal distributions of the phytoplankton and their relationships to physico-chemical environmental factors in the western Jinhae Bay, Korea from November 2003 to August 2004. In most cases, physico-chemical environmental factors showed homogeneous distribution. The phytoplankton communities were composed of mainly diatoms and dinoflagellates, and their standing crops ranged from $16{\times}10^3\;cells\;l^{-1}\;to\;5,845{\times}10^3\;cells\;l^{-1}$ (with a mean value of $555{\times}10^3\;cells\;l^{-1}$). The bloom of phytoplankton was observed in Gohyun Port in the summer. Seasonal variation of phytoplankton standing crops was higher in winter and summer than in spring and autumn. The dominant species were Skeletonema costatum, Akashiwo sanguinea, Pseudo-nitzschia pungens, Dactyliosolen sp., Leptocylindrus danicus, cryptomonads and etc. Especially, S. costatum was predominant in the summer and A. sanguinea (spring and autumn), Pseudo-nitzschia sp. (summer), Guinardia striata (spring), unidentified flagellates (summer) and cryptomonads (spring) appeared to be an opportunistic species. Concentrations of Chl a ranged from $0.6{\mu}g{\cdot}l^{-1}\;to\;16.7{\mu}g{\cdot}l^{-1}$ (with a mean value of $3.4{\mu}g{\cdot}l^{-1}$). The results of the canonical correspondence analysis implies the study area was grouped into the 2 water masses (inner and outer waters of Gohyun Port) and inner waters had higher abundance and Chl a concentration than outer waters. Also, phytoplankton sanding crops were related with temperature, DO and nutrients ($SiO^2$, TN, TP and etc.) in inner waters. Inner water-mass of Gohyun Port expanded between Gacho Is. and Chilchon Is. during the winter.

• Korean Journal of Ecology and Environment
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• v.37 no.1 s.106
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• pp.26-35
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• 2004

We investigated the effect of physicochemical environmental factors on the community dynamics of phytoplanktons and bacteria at the Hoeya Dam Reservoir, a drinking water reservoir for Ulsan city. Water samples were collected and analyzed every two to four weeks at three sites along the reservoir from April to October, 2001. During the study period, the Secchi depths were between 0.4 and 3.5 m. At the surface layer of water column, temperature ranged 10.2 ~ $32.0^{\circ}C$, pH 7.3${\sim}$9.6, dissolved oxygen 5.5 ${\sim}$ 12.4 mg $L^{-1}$, $BOD_5$ 0.8 ${\sim}$ 5.0 mg $L^{-1}$, $COD_{Mn}$ 3.7 ${\sim}$ 10.0 mg $L^{-1}$, and Chl-a 8.9 ${\sim}$ 60.9 mg $m^{-3}$. At the bottom layer, temperature varied 7.2 ${\sim}$ $28.9^{\circ}C$, pH 7.1 ${\sim}$ 9.3, dissolved oxygen 0.6 ${\sim}$ 9.7 mg $L^{-1}$, $BOD_5$ 0.8 ${\sim}$ 4.5 mg $L^{-1}$, $COD_{Mn}$ 3.9 ${\sim}$ 10.0 mg $L^{-1}$, and Chl-a 4.3 ${\sim}$ 81.9 mg $m^{-3}$. The numbers of phytoplanktons were 7.4${\pm}10^2{\sim}2.6{\pm}10^5$ cells $mL^{-1}$ at surface and 2.5${\pm}10^2{\sim}2.4{\pm}10^4$ cells $mL^{-1}$ at bottom, and were positively correlated with water temperature and Chl- a concentration. Genus Stephanodiscus and genus Oscillatoria dominated on April and on May, respectively. Cyanobacterial blooms of Aphanizomenon, Microcystis, Anabaena were observed from June to early September, and thereafter Stephanodiscus and Aulacoseiral dominated again. Total microbial counts ranged 1.73${\pm}10^4{\sim}1.68{\pm}10^5$ cells $mL^{-1}$, and were positively correlated with water temperature and phytoplankton counts at surface water. Heterotrophic plate counts (HPCs) ranged 30${\sim}4.1{\pm}10^3$ CFU $mL^{-1}$, and were positively correlated with $BOD_5$ and $NO^3\;^-$-N concentration at bottom water. Unlike the total microbial counts, the numbers of fecal coliforms and fecal streptococci as well as HPCs were higher at the bottom than the surface layer and were highest at the upper a site among the three sampling sites. Since the concentrations of fecal coliforms and streptococci were still high at the bottom of site c, where intake for water treatment plant is located, it appeared that special management of water treatment processes may be needed especially after strong rainfall.

• Korean Journal of Environmental Biology
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• v.22
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• pp.54-62
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• 2004

We examined the impacts of anthyopogenic pollutant (benzo〔a〕pyrene) on the growth and photosynthesis of five marine phytoplankton species (Skeletonema costatum, Heterosigma akashiwo, Prorocentrum dentatum, P. minimum, Aknshiwo sanguinea), which are dominant in Korean coastal water. After the 72 h exposure to benzo〔a〕pyrene, the dramatic decrease in cell numbers was observed in the range of 1 to 10 $\mu\textrm{g}$ L$^{-1}$ for S. costatum, P. minimum, P. dentatum, whereas for A. sanguinea and H. akashiwo at the low concentrations 0.1 to 1 $\mu\textrm{g}$ L$^{-1}$ . Among the 5 phytoplankton species, the highest growth inhibition concentration ($IC_{50}$/) was 6.20 $\mu\textrm{g}$ L$^{-1}$ for P. minimum, followed by 2.14 $\mu\textrm{g}$ L$^{-1}$ for P. dentatum, 1.68 $\mu\textrm{g}$ L$^{-1}$ for S. costatum, 0.74 $\mu\textrm{g}$ L$^{-1}$ for H. akashiwo, 0.10 $\mu\textrm{g}$ L$^{-1}$ for A. sanguinea. The five species exposed to the low concentration of 1 $\mu\textrm{g}$ L$^{-1}$ were recovered after transferring to new media, but the species exposed to the high concentrations of 10 and 100 $\mu\textrm{g}$ L$^{-1}$ were not recovered, with the exception of P. minimum. Those results indicate that the thecate dinoflagellate P. minimum is most tolerant to the chemical and the athecate dinoflagellate A. sanguinea is not. Geneyally, the cell-specific photosynthetic capacity of H. akashiwo exposed to the low concentrations of 0.1 and 1 $\mu\textrm{g}$ L$^{-1}$ was higher than that of the cells in the control, whereas the cells exposed to the high concentrations of 5 and 10 $\mu\textrm{g}$ L$^{-1}$ showed the negligible photosynthetic level by the first few days of the experiment. In the case of the cells exposed to the concentration of 5 $\mu\textrm{g}$ L$^{-1}$ , after 12 days of the experiment the photosynthetic capacity was increased toward the end of the experiment. This indicates that H. akashiwo may utilize the benzo〔a〕pyrene as a carton source for its growth when exposed to low concentrations. Results suggest that anthropogenic pollutants such as benzo〔a〕pyrene may have significant influence on the succession of phytoplankton species composition and the primary production in coastal marine environments.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.